Microgrids with distributed renewable energy sources are especially sensitive to power
quality disturbances. To mitigate the effects of distortions, they must first be detected and …

Nowadays, the main grid is facing several challenges related to the integration of renewable
energy resources, deployment of grid-level energy storage devices, deployment of new …

The vibration data, especially those collected during the system run-up and run-down
periods, contain rich information for gearbox condition monitoring. Time–frequency (TF) …

Unauthorized network access and spoofing attacks at wireless access points (WAPs) have
been traditionally addressed using bit-centric security measures and remain a major …

This paper presents a novel approach to detect and classify the power quality disturbance
(PQD) signals based on singular spectrum analysis (SSA), curvelet transform (CT) and deep …

Recently, electroencephalography (EEG) signals have shown great potential for emotion
recognition. Nevertheless, multichannel EEG recordings lead to redundant data …

Electric power utilities employ “smart” re-closing devices capable of capturing electrical
disturbance (ED) waveforms in real-time. These waveforms are digitally sampled …

Abstract Structure and function go hand in hand. However, while a complex structure can be
relatively safely broken down into the minutest parts, and technology is now delving into …

In this paper, information entropy and ensemble learning based signal recognition theory
and algorithms have been proposed. We have extracted 16 kinds of entropy features out of 9 …

This paper proposes an advanced Internet of Things (IoT) system for measuring, monitoring,
and recording some power quality (PQ) parameters. The proposed system is designed and …